Using Connectivity to Explain Autism

Mapping Intimacies ◽

10.31234/osf.io/6rqdp ◽

2019 ◽

Author(s):

Jack Adamek ◽

Yu Luo ◽

Joshua Ewen

Keyword(s):

Scientific Explanation ◽

Causal Explanation ◽

Autism Spectrum ◽

Imaging Method ◽

Imaging Data ◽

Reverse Engineer ◽

Physiological Processes ◽

The Mind ◽

The Brain

The chapters in this Handbook reveal the breadth of brilliant imaging and analysis techniques designed to fulfill the mandate of cognitive neuroscience: to understand how anatomical structures and physiological processes in the brain cause typical and atypical behavior. Yet merely producing data from the latest imaging method is insufficient to truly achieve this goal. We also need a mental toolbox that contains methods of inference that allow us to derive true scientific explanation from these data. Causal inference is not easy in the human brain, where we are limited primarily to observational data and our methods of experimental perturbation in the service of causal explanation are limited. As a case study, we reverse engineer one of the most influential accounts of a neuropsychiatric disorder that is derived from observational imaging data: the connectivity theories of autism spectrum disorder (ASD). We take readers through an approach of first considering all possible causal paths that are allowed by preliminary imaging-behavioral correlations. By progressively sharpening the specificity of the measures and brain/behavioral constructs, we iteratively chip away at this space of allowable causal paths, like the sculptor chipping away the excess marble to reveal the statue. To assist in this process, we consider how current imaging methods that are lumped together under the rubric of “connectivity” may actually offer a differentiated set of connectivity constructs that can more specifically relate notions of information transmission in the mind to the physiology of the brain.

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Patterns of brain asymmetry associated with polygenic risks for autism and schizophrenia implicate language and executive functions but not brain masculinization

10.1101/2021.03.19.436120 ◽

2021 ◽

Author(s):

Zhiqiang Sha ◽

Dick Schijven ◽

Clyde Francks

Keyword(s):

Sex Differences ◽

Executive Functions ◽

Autism Spectrum ◽

Brain Asymmetry ◽

Risk Scores ◽

Imaging Data ◽

Polygenic Risk ◽

Left Right Asymmetry ◽

The Uk ◽

The Brain

AbstractAutism spectrum disorder (ASD) and schizophrenia have been conceived as partly opposing disorders in terms of systemizing versus empathizing cognitive styles, with resemblances to male versus female average sex differences. Left-right asymmetry of the brain is an important aspect of its organization that shows average differences between the sexes, and can be altered in both ASD and schizophrenia. Here we mapped multivariate associations of polygenic risk scores (PRS) for ASD and schizophrenia with asymmetries of regional cerebral cortical surface area, thickness and subcortical volume measures in 32,256 participants from the UK Biobank. PRS for the two disorders were positively correlated (r=0.08, p=7.13×10−50), and both were higher in females compared to males, consistent with biased participation against higher-risk males. Each PRS was associated with multivariate brain asymmetry after adjusting for sex, ASD PRS r=0.03, p=2.17×10−9, schizophrenia PRS r=0.04, p=2.61×10−11, but the multivariate patterns were mostly distinct for the two PRS, and neither resembled average sex differences. Annotation based on meta-analyzed functional imaging data showed that both PRS were associated with asymmetries of regions important for language and executive functions, consistent with behavioural associations that arose in phenome-wide association analysis. Overall, the results indicate that distinct patterns of subtly altered brain asymmetry may be functionally relevant manifestations of polygenic risk for ASD and schizophrenia, but do not support brain masculinization or feminization in their etiologies.

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Ways of the Mind

The Oxford Handbook of the Phenomenology of Music Cultures ◽

10.1093/oxfordhb/9780190693879.013.4 ◽

2021 ◽

Author(s):

Dotan Nitzberg ◽

Michael B. Bakan

Keyword(s):

Autism Spectrum ◽

Concert Pianist ◽

The Mind

This chapter proposes a progressive approach to research at the intersection of autism studies and music studies, one through which scientific frames of objectivity-aspiring, anonymizing representation are replaced by ethnographic and phenomenological frames of personhood-aspiring, individual re-presentation. Through a case study of the musical experiences of first author Dotan Nitzberg, a concert pianist on the autism spectrum, and through the re-presentation of dialogues between Nitzberg and the chapter’s second author, ethnomusicologist Michael Bakan, the commonplace practice of objectifying and dehumanizing autistic individuals, including musicians, is challenged. The authors posit that phenomenological approaches, and those informed by a Levinasian philosophy of alterity in particular, have the capacity to leverage this challenge in affirming the agency and humanity of people on the autism spectrum, fostering an appreciation for their difference and contributing to a larger activist agenda of reducing the stigma and marginalization to which they have historically been subjected.

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Mapping the brain to harness the mind: Using behavioural and imaging data to inform educational practice

Frontiers in Neuroscience ◽

10.3389/conf.fnins.2016.92.00002 ◽

2016 ◽

Vol 10 ◽

Author(s):

Boudelaa Sami

Keyword(s):

Educational Practice ◽

Imaging Data ◽

The Mind ◽

The Brain

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Neuromeditation: The Science and Practice of Combining Neurofeedback and Meditation for Improved Mental Health

Smart Biofeedback - Perspectives and Applications ◽

10.5772/intechopen.93781 ◽

2020 ◽

Author(s):

Jeff Tarrant

Keyword(s):

Mental Health ◽

Early Research ◽

Eeg Biofeedback ◽

Treatment Intervention ◽

States Of Consciousness ◽

Original Case ◽

The Mind ◽

Anxiety Depression ◽

The Brain

Beginning meditators often complain that they do not know if they are “doing it right” or give up before realizing significant benefits. Advanced meditators often reach a plateau and struggle to reach “the next level” of their practice. Modern researchers and practitioners are finding a possible new solution to these challenges by using EEG biofeedback to increase awareness of subtle states of consciousness and speed the learning process. By tracking brainwave activity in specific regions of the brain, we can tell if someone is focused or relaxed. We can tell if the mind is wandering, if they are engaged in body-based emotions, or if they have entered a space of internal quiet. By monitoring this activity and connecting it directly to the intent of the meditation, it is possible to help meditators learn to quickly enter a desired state of consciousness and maintain this state for increasing periods of time. This chapter will describe the early research conducted in this area along with an original case study conducted by the author. In addition, the author will describe the way this technology is being used as a treatment intervention for ADHD, anxiety, depression, and PTSD.

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Microglial and Astrocytic Function in Physiological and Pathological Conditions: Estrogenic Modulation

International Journal of Molecular Sciences ◽

10.3390/ijms21093219 ◽

2020 ◽

Vol 21 (9) ◽

pp. 3219 ◽

Cited By ~ 2

Author(s):

Andrea Crespo-Castrillo ◽

Maria-Angeles Arevalo

Keyword(s):

Neurological Diseases ◽

Autism Spectrum ◽

Sexual Differences ◽

Main Role ◽

Cell Functions ◽

Physiological Processes ◽

Males And Females ◽

The Brain ◽

Lateral Sclerosis

There are sexual differences in the onset, prevalence, and outcome of numerous neurological diseases. Thus, in Alzheimer’s disease, multiple sclerosis, and major depression disorder, the incidence in women is higher than in men. In contrast, men are more likely to present other pathologies, such as amyotrophic lateral sclerosis, Parkinson’s disease, and autism spectrum. Although the neurological contribution to these diseases has classically always been studied, the truth is that neurons are not the only cells to be affected, and there are other cells, such as glial cells, that are also involved and could be key to understanding the development of these pathologies. Sexual differences exist not only in pathology but also in physiological processes, which shows how cells are differentially regulated in males and females. One of the reasons these sexual differences may occur could be due to the different action of sex hormones. Many studies have shown an increase in aromatase levels in the brain, which could indicate the main role of estrogens in modulating proinflammatory processes. This review will highlight data about sex differences in glial physiology and how estrogenic compounds, such as estradiol and tibolone, could be used as treatment in neurological diseases due to their anti-inflammatory effects and the ability to modulate glial cell functions.

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A computational toolbox and step-by-step tutorial for the analysis of neuronal population dynamics in calcium imaging data

10.1101/103879 ◽

2017 ◽

Cited By ~ 2

Author(s):

Sebastián A. Romano ◽

Verónica Pérez-Schuster ◽

Adrien Jouary ◽

Alessia Candeo ◽

Jonathan Boulanger-Weill ◽

...

Keyword(s):

Population Dynamics ◽

Calcium Imaging ◽

Single Neuron ◽

Neuronal Population ◽

Population Coding ◽

Imaging Data ◽

Neuronal Responses ◽

Population Activity ◽

The Brain

The development of new imaging and optogenetics techniques to study the dynamics of large neuronal circuits is generating datasets of unprecedented volume and complexity, demanding the development of appropriate analysis tools. We present a tutorial for the use of a comprehensive computational toolbox for the analysis of neuronal population activity imaging. It consists of tools for image pre-processing and segmentation, estimation of significant single-neuron single-trial signals, mapping event-related neuronal responses, detection of activity-correlated neuronal clusters, exploration of population dynamics, and analysis of clusters’ features against surrogate control datasets. They are integrated in a modular and versatile processing pipeline, adaptable to different needs. The clustering module is capable of detecting flexible, dynamically activated neuronal assemblies, consistent with the distributed population coding of the brain. We demonstrate the suitability of the toolbox for a variety of calcium imaging datasets, and provide a case study to explain its implementation.

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The Role of Structure MRI in Diagnosing Autism

Diagnostics ◽

10.3390/diagnostics12010165 ◽

2022 ◽

Vol 12 (1) ◽

pp. 165

Author(s):

Mohamed T. Ali ◽

Yaser ElNakieb ◽

Ahmed Elnakib ◽

Ahmed Shalaby ◽

Ali Mahmoud ◽

...

Keyword(s):

Cerebral Cortex ◽

Data Exchange ◽

Structural Mri ◽

Brain Regions ◽

Autism Spectrum ◽

Accuracy Score ◽

Imaging Data ◽

Cad System ◽

Feature Values ◽

The Brain

This study proposes a Computer-Aided Diagnostic (CAD) system to diagnose subjects with autism spectrum disorder (ASD). The CAD system identifies morphological anomalies within the brain regions of ASD subjects. Cortical features are scored according to their contribution in diagnosing a subject to be ASD or typically developed (TD) based on a trained machine-learning (ML) model. This approach opens the hope for developing a new CAD system for early personalized diagnosis of ASD. We propose a framework to extract the cerebral cortex from structural MRI as well as identifying the altered areas in the cerebral cortex. This framework consists of the following five main steps: (i) extraction of cerebral cortex from structural MRI; (ii) cortical parcellation to a standard atlas; (iii) identifying ASD associated cortical markers; (iv) adjusting feature values according to sex and age; (v) building tailored neuro-atlases to identify ASD; and (vi) artificial neural networks (NN) are trained to classify ASD. The system is tested on the Autism Brain Imaging Data Exchange (ABIDE I) sites achieving an average balanced accuracy score of 97±2%. This paper demonstrates the ability to develop an objective CAD system using structure MRI and tailored neuro-atlases describing specific developmental patterns of the brain in autism.

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